Retail analytics in Power BI


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The retail markets have become extensively competitive and each player in the retail market is striving for the ability to optimize the marketing serving processes, while satisfying the customer expectations. Therefore, it is important for any business/firm to manage and channelize the data to achieve the customer’s delight as well as in generating the healthy profits. With regard to big retail players internationally as well as in the USA, data mining or rather big data analytics is now being at every single stage of the retail market/business process, i.e., tracking customer order placements and predicting the forecast sales of the particular product, optimizing the product sales and the offers based on consumer preferences, tracking the emerging products in the market, forecasting and predicting the sales and future demand based on the predictive simulation tools. In parallel to this, recognizing the customers’ expectations and interest in specific product types based on their previous purchase actions, and working out the best technique to approach them through targeted marketing efforts and ultimately what to sell them next in what configures the core of data analytics. This project is the outcome of a descriptive research on the past, present, and future of retail industry and the application of business analytics in shaping appropriate marketing strategies with data sources, data structures, and DAX query language through dashboard in Power BI. The project aims to show on how we can use the Power BI with business oriented retail analytics data using DAX query language and its performance on presenting the dashboard to the end users. So in this project, I have created an analytical dashboard to know historic trend and business performance, and also to know which products are sold mostly, which are the top regions and managers/market performance. Additionally, I have created what if analysis for future planning on the basis of historic trend - this dashboard is created for stake holders to know business growth trend and functional areas and with the visualizations. This project represents the large dataset into visualization form to quickly see the performances of all the commodities.



Retail analysis, Data analytics, Power BI, Big data analytics

Graduation Month



Master of Science


Department of Computer Science

Major Professor

Daniel A. Andresen